CN113973793A - Unmanned aerial vehicle spraying treatment method and system for pest and disease damage area - Google Patents
Unmanned aerial vehicle spraying treatment method and system for pest and disease damage area Download PDFInfo
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- CN113973793A CN113973793A CN202111056734.8A CN202111056734A CN113973793A CN 113973793 A CN113973793 A CN 113973793A CN 202111056734 A CN202111056734 A CN 202111056734A CN 113973793 A CN113973793 A CN 113973793A
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0025—Mechanical sprayers
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0089—Regulating or controlling systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64D—EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENTS OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT
- B64D1/00—Dropping, ejecting, releasing, or receiving articles, liquids, or the like, in flight
- B64D1/16—Dropping or releasing powdered, liquid, or gaseous matter, e.g. for fire-fighting
- B64D1/18—Dropping or releasing powdered, liquid, or gaseous matter, e.g. for fire-fighting by spraying, e.g. insecticides
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/30—Against vector-borne diseases, e.g. mosquito-borne, fly-borne, tick-borne or waterborne diseases whose impact is exacerbated by climate change
Abstract
The application discloses unmanned aerial vehicle sprays processing method and system in plant diseases and insect pests area, and this method includes: acquiring a first photo of each of a plurality of areas of an area to be sprayed, wherein the first photo is a photo of each of the plurality of areas before pesticide is not sprayed; acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area; comparing the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture; and determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result. Through this application, solved the problem that can't accomplish reasonable aassessment to the effect after unmanned aerial vehicle sprays insecticide among the prior art to the effect of spraying the operation to unmanned aerial vehicle assesses, provides data support for formulating the reasonable plan of spraying insecticide of unmanned aerial vehicle.
Description
Technical Field
The application relates to the field of unmanned aerial vehicle control, in particular to a spraying treatment method and system for an unmanned aerial vehicle in a pest and disease area.
Background
In the current crop production process, various insect pests are easily suffered, and the crop yield is seriously influenced. In order to effectively control pest disasters, protect the healthy growth of crops and improve the yield, pesticides need to be sprayed on the crops to kill pests and the like. Traditional agricultural plant protection is mainly operated manually and semi-mechanically, and operators spray the agricultural chemical by experience, so that the labor intensity is high, the agricultural chemical is wasted, and the direct contact of the agricultural chemical has great harm to the bodies of the operators.
In order to solve the great problem of the operation personnel harm of manual operation right, now generally use unmanned aerial vehicle to carry out spraying of pesticide, generally spray according to set route when using unmanned aerial vehicle to carry out spraying of pesticide, do not carry out reasonable aassessment to the effect after unmanned aerial vehicle sprays.
Disclosure of Invention
The embodiment of the application provides a spraying treatment method and system for unmanned aerial vehicles in pest and disease areas, and aims to solve the problem that reasonable evaluation cannot be achieved for the effect of the unmanned aerial vehicles after pesticide spraying in the prior art.
According to one aspect of the application, an unmanned aerial vehicle spraying treatment method for a pest area is provided, and comprises the following steps: acquiring a first photo of each of a plurality of areas of an area to be sprayed, wherein the area to be sprayed is an area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before the pesticide is not sprayed; acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area; comparing the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture; and determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
Further, before the obtaining the second photo of each region, the method further includes: acquiring a first pesticide spraying plan; sending a flight control part in the first pesticide spraying plan to an unmanned aerial vehicle, wherein the flight control part is used for controlling flight parameters of the unmanned aerial vehicle in a spraying process; and sending a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way, wherein the pesticide formula part is a formula of pesticide loaded into the unmanned aerial vehicle for spraying.
Further, after determining that the second pesticide spraying needs to be performed on the area corresponding to the second photo according to the comparison result, the method further includes: acquiring geographical position information of an area corresponding to the second photo; determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture; and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle.
Further, the flight parameters include at least one of: flight path, flight speed, time spent in a predetermined area, spray speed.
Further, obtaining the first pesticide spray plan includes: and acquiring the first pesticide spraying plan according to the pest and disease damage condition in the first picture.
According to another aspect of this application, still provide an area unmanned aerial vehicle of plant diseases and insect pests sprays processing system, include: the device comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring a first photo of each of a plurality of areas of an area to be sprayed, the area to be sprayed is the area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before the pesticide is not sprayed; the second acquisition module is used for acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area; a first determining module, configured to compare the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture; and the second determining module is used for determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
Further, still include: the transmission module is used for acquiring a first pesticide spraying plan and transmitting a flight control part in the first pesticide spraying plan to the unmanned aerial vehicle, wherein the flight control part is used for controlling the unmanned aerial vehicle to transmit a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way at the flight parameter of a spraying process, wherein the pesticide distribution part is filled in the formula of the pesticide sprayed by the unmanned aerial vehicle.
Further, after determining that the second pesticide spraying needs to be performed on the area corresponding to the second photo according to the comparison result, the sending module is further configured to: acquiring geographical position information of an area corresponding to the second photo; determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture; and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle.
Further, the flight parameters include at least one of: flight path, flight speed, time spent in a predetermined area, spray speed.
Further, the sending module is used for obtaining the first pesticide spraying plan according to the pest and disease damage condition in the first picture.
In the embodiment of the application, a first photo of each of a plurality of areas of an area to be sprayed is obtained, wherein the area to be sprayed is an area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before pesticide is not sprayed; acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area; comparing the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture; and determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result. Through this application, solved the problem that can't accomplish reasonable aassessment to the effect after unmanned aerial vehicle sprays insecticide among the prior art to the effect of spraying the operation to unmanned aerial vehicle assesses, provides data support for formulating the reasonable plan of spraying insecticide of unmanned aerial vehicle.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
fig. 1 is a flow chart of an unmanned aerial vehicle spraying treatment method for a pest area according to an embodiment of the application.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
In this embodiment, a pest and disease area unmanned aerial vehicle spraying treatment method is provided, fig. 1 is a flowchart of the pest and disease area unmanned aerial vehicle spraying treatment method according to the embodiment of the present application, and as shown in fig. 1, the flowchart includes the following steps:
step S102, acquiring a first photo of each of a plurality of areas of an area to be sprayed, wherein the area to be sprayed is an area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before pesticide is not sprayed;
step S104, acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticides on the area;
step S106, comparing the second picture with the first picture to determine that the pest and disease damage in the second picture is reduced relative to the pest and disease damage in the first picture;
and S108, determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
Through the steps, the problem that reasonable evaluation cannot be achieved for the effect after the unmanned aerial vehicle sprays the pesticide in the prior art is solved, so that the effect of spraying operation on the unmanned aerial vehicle is evaluated, and data support is provided for formulating a reasonable pesticide spraying plan of the unmanned aerial vehicle.
The pesticide spraying plan of the unmanned aerial vehicle can be automatically generated, the steps can be executed through preset software, and the software can also obtain the pesticide spraying plan, for example, obtain a first pesticide spraying plan; sending a flight control part in the first pesticide spraying plan to an unmanned aerial vehicle, wherein the flight control part is used for controlling flight parameters of the unmanned aerial vehicle in a spraying process; and sending a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way, wherein the pesticide formula part is a formula of pesticide loaded into the unmanned aerial vehicle for spraying.
The first pesticide spraying plan can be made in various ways, for example, the first pesticide spraying plan is obtained according to the pest and disease condition in the first picture.
There are many ways to obtain the first spraying plan, and in an alternative embodiment, the type of pest and disease damage and the density of pest and disease damage in the first picture can be obtained; determining a formula of a pesticide according to the type of the pest and disease damage, and determining the spraying amount of the pesticide in the area corresponding to the first picture according to the density of the pest and disease damage, wherein the spraying amount is used for determining the spraying time of the unmanned aerial vehicle in the area corresponding to the first picture.
The first pesticide spray plan may be obtained in this embodiment using machine learning.
For example, the first machine learning engine may be trained using a plurality of sets of first training data, each set of first training data including input data and output data, wherein the input data includes a photograph of a crop area with a pest, and the output data is a type of pest and a density of pest in the photograph of the input data.
In this alternative embodiment, a second machine learning engine may be trained using a plurality of sets of second training data, each set of second training data comprising input data and output data, wherein the input data is a density of pests and a formulation of pesticides to be sprayed, and the output data comprises an amount of pesticides to be sprayed per unit area.
The pesticide spraying formula comprises the concentration of the pesticide, the concentration is determined according to the pest and disease density, and the concentration can be determined according to the relation between the pre-configured concentration of the pesticide and the pest and disease density.
After the first machine learning engine outputs the type and the density of the pest and disease damage according to the input picture, the software acquires a pesticide formula according to the type of the pest and disease damage, wherein the pesticide formula comprises the components and the concentration of the pesticide; and then sending the density of the plant diseases and insect pests and the formula to a second machine learning engine, acquiring output data of the second machine learning engine, and obtaining the first pesticide spraying plan according to the area of a first area corresponding to the first picture and the amount of pesticide to be sprayed on the unit surface.
After determining that the second pesticide spraying is required to be performed on the area corresponding to the second photo according to the comparison result, the software may further make a pesticide spraying plan again, and in this embodiment, the geographical location information of the area corresponding to the second photo may be acquired; determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture; and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle. The flight parameters may include at least one of: flight path, flight speed, time spent in a predetermined area, spray speed.
As an optional embodiment, a correspondence relationship between the finally executed pesticide spraying plan and the information of the area to be sprayed is saved, wherein the information of the area to be sprayed includes: area, plant type, pest density, manner of dividing the area to be sprayed into a plurality of areas, and the like. And after determining that the second pesticide spraying is not needed according to the comparison result, the finally executed pesticide spraying technology is the first pesticide spraying plan, after the second pesticide spraying is needed, the first pesticide spraying plan is adjusted according to the second pesticide spraying plan, and the adjusted first pesticide spraying plan is used as the finally executed pesticide spraying plan.
After the corresponding relation is stored, the information of the area to be sprayed can be input by acquiring the first pesticide spraying plan, and the finally executed pesticide spraying plan corresponding to the spraying area closest to the information of the area to be sprayed is matched in the stored corresponding relation according to the information of the area to be sprayed.
There are many matching ways, each parameter of the information of the spraying area can be scored for 1 to 10 points, the scores of each parameter are added to obtain the score of the spraying area, and the spraying area with the closest score difference in the area is found. For example, the higher the area size is about close to the score; the plant species belonging to the same plant species is divided into 10 parts, 5 parts in the same genus, or 0 part; the types of the pests and the diseases are 10 points if the types are the same, and 0 point if the types are different, wherein the types of the pests and the diseases are classified according to pesticides, namely the pests and the diseases which can be killed by the same pesticide are the same type of pests and diseases; the higher the pest density is, the higher the score is; the higher the number of multiple regions the higher the score, and so on.
In the above embodiment, for the area to be sprayed, the pesticide spraying plan corresponding to the already completed spraying area whose score difference is within the predetermined range is first searched according to the previously stored correspondence, and if the pesticide spraying plan is found, the pesticide spraying plan is used as the plan executed by the area to be sprayed, and if the spraying of the second spraying plan is executed after the execution is completed, the correspondence is stored. And if the spraying plans with the scores within the preset range are not found, generating a first spraying plan by using the first machine learning engine and the second machine learning engine.
In this embodiment, an electronic device is provided, comprising a memory in which a computer program is stored and a processor configured to run the computer program to perform the method in the above embodiments.
The programs described above may be run on a processor or may also be stored in memory (or referred to as computer-readable media), which includes both non-transitory and non-transitory, removable and non-removable media, that implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
These computer programs may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks, and corresponding steps may be implemented by different modules.
Such an apparatus or system is provided in this embodiment. This system is called regional unmanned aerial vehicle of plant diseases and insect pests and sprays processing system, and this system includes: the device comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring a first photo of each of a plurality of areas of an area to be sprayed, the area to be sprayed is the area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before the pesticide is not sprayed; the second acquisition module is used for acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area; a first determining module, configured to compare the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture; and the second determining module is used for determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
The system or the apparatus is used for implementing the functions of the method in the foregoing embodiments, and each module in the system or the apparatus corresponds to each step in the method, which has been described in the method and is not described herein again.
For example, the system may further include: the transmission module is used for acquiring a first pesticide spraying plan and transmitting a flight control part in the first pesticide spraying plan to the unmanned aerial vehicle, wherein the flight control part is used for controlling the unmanned aerial vehicle to transmit a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way at the flight parameter of a spraying process, wherein the pesticide distribution part is filled in the formula of the pesticide sprayed by the unmanned aerial vehicle.
For another example, after determining that the second pesticide spraying needs to be performed on the area corresponding to the second photo according to the comparison result, the sending module may be further configured to: acquiring geographical position information of an area corresponding to the second photo; determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture; and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle. Optionally, the sending module is configured to obtain the first pesticide spraying plan according to the pest and disease damage condition in the first picture.
The problem of the effect after spraying insecticide to unmanned aerial vehicle can't accomplish reasonable aassessment among the prior art is solved through above-mentioned embodiment to the effect of spraying the operation to unmanned aerial vehicle assesses, provides data support for formulating the reasonable pesticide spray plan of unmanned aerial vehicle.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. An unmanned aerial vehicle spraying treatment method for a pest and disease damage area is characterized by comprising the following steps:
acquiring a first photo of each of a plurality of areas of an area to be sprayed, wherein the area to be sprayed is an area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before the pesticide is not sprayed;
acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area;
comparing the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture;
and determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
2. The method of claim 1, further comprising, prior to obtaining the second photograph of each region:
acquiring a first pesticide spraying plan;
sending a flight control part in the first pesticide spraying plan to an unmanned aerial vehicle, wherein the flight control part is used for controlling flight parameters of the unmanned aerial vehicle in a spraying process;
and sending a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way, wherein the pesticide formula part is a formula of pesticide loaded into the unmanned aerial vehicle for spraying.
3. The method of claim 2, further comprising, after determining that the second pesticide spray is required to the area corresponding to the second photograph based on the comparison,:
acquiring geographical position information of an area corresponding to the second photo;
determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture;
and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle.
4. The method of claim 2, wherein the flight parameter comprises at least one of: flight path, flight speed, time spent in a predetermined area, spray speed.
5. The method of any one of claims 2 to 4, wherein obtaining the first pesticide spray plan comprises:
and acquiring the first pesticide spraying plan according to the pest and disease damage condition in the first picture.
6. The utility model provides an area unmanned aerial vehicle of plant diseases and insect pests sprays processing system which characterized in that includes:
the device comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring a first photo of each of a plurality of areas of an area to be sprayed, the area to be sprayed is the area to be sprayed with pesticide, the area to be sprayed is the plurality of areas, and the first photo is a photo of each of the plurality of areas before the pesticide is not sprayed;
the second acquisition module is used for acquiring a second photo of each area, wherein the second photo is a photo of each area in the plurality of areas after the unmanned aerial vehicle sprays pesticide on the area;
a first determining module, configured to compare the second picture with the first picture to determine that the pest in the second picture is reduced relative to the pest in the first picture;
and the second determining module is used for determining whether to carry out secondary pesticide spraying on the area corresponding to the second picture again according to the comparison result.
7. The system of claim 6, further comprising:
the transmission module is used for acquiring a first pesticide spraying plan and transmitting a flight control part in the first pesticide spraying plan to the unmanned aerial vehicle, wherein the flight control part is used for controlling the unmanned aerial vehicle to transmit a pesticide distribution part in the first pesticide spraying plan to a pre-configured contact way at the flight parameter of a spraying process, wherein the pesticide distribution part is filled in the formula of the pesticide sprayed by the unmanned aerial vehicle.
8. The system of claim 7, wherein after determining that the second pesticide spray is required to the area corresponding to the second photograph based on the comparison, the sending module is further configured to:
acquiring geographical position information of an area corresponding to the second photo; determining flight parameters in a second pesticide spraying plan which is executed again according to the geographical position information, wherein flight paths in the flight parameters are determined according to the geographical position information of the area corresponding to the second picture; and sending the flight parameters in the second pesticide spraying plan to the unmanned aerial vehicle.
9. The system of claim 7, wherein the flight parameters include at least one of: flight path, flight speed, time spent in a predetermined area, spray speed.
10. The system according to any one of claims 7 to 9,
the sending module is used for obtaining the first pesticide spraying plan according to the pest and disease damage condition in the first picture.
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| CN109446958A (en) * | 2018-10-18 | 2019-03-08 | 广州极飞科技有限公司 | Determination method and device, the system of pesticide supplying effect |
| CN109445457A (en) * | 2018-10-18 | 2019-03-08 | 广州极飞科技有限公司 | Determination method, the control method and device of unmanned vehicle of distributed intelligence |
| US20210078706A1 (en) * | 2019-09-12 | 2021-03-18 | Huan-Jung Lin | Precision agriculture implementation method by uav systems and artificial intelligence image processing technologies |
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| CN111459183A (en) * | 2020-04-10 | 2020-07-28 | 广州极飞科技有限公司 | Operation parameter recommendation method and device, unmanned equipment and storage medium |
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